Assessing the Validity of Brain Glucose Concentration Measurement Using Microdialysis

Brain functions, such as learning, orchestrating locomotion, memory recall, and processing information, all require glucose as a source of energy. During these functions, the glucose concentration decreases as the glucose is being consumed by brain cells. By measuring this drop in concentration, it is possible to determine which parts of the brain are used during specific functions and consequently, how much energy the brain requires to complete the function. One way to measure in vivo brain glucose levels is with a microdialysis probe. The drawback of this analytical procedure, as with many steadystate fluid flow systems, is that the probe fluid will not reach equilibrium with the brain fluid. Therefore, brain concentration is inferred by taking samples at multiple inlet glucose concentrations and finding a point of convergence. The goal of this thesis is to create a three-dimensional, time-dependent, finite element representation of the brainprobe system in COMSOL 4.2 that describes the diffusion and convection of glucose. Once validated with experimental results, this model can then be used to test parameters that experiments cannot access. When simulations were run using published values for physical constants (i.e. diffusivities, density and viscosity), the resulting glucose model concentrations were within the error of the experimental data. This verifies that the model is an accurate representation of the physical system. In addition to accurately describing the experimental brain-probe system, the model I created is able to show the validity of zero-net-flux for a given experiment. A useful discovery is that the slope of the zero-net-flux line is dependent on perfusate flow rate and diffusion coefficients, but it is independent of brain glucose concentrations. The model was simplified with the realization that the perfusate is at thermal equilibrium with the brain throughout the active region of the probe. This allowed for the assumption that all model parameters are temperature independent. The time to steady-state for the probe is approximately one minute. However, the signal degrades in the exit tubing due to Taylor dispersion, on the order of two minutes for two meters of tubing. Given an analytical instrument requiring a five μL aliquot, the smallest brain process measurable for this system is 13 minutes.

Microbial community analysis of Lake Chillisquaque, a small water system in Central Pennsylvania

Cyanobacteria are photosynthetic organisms that require the absorption of light for the completion of photosynthesis. Cyanobacteria can use a variety of wavelengths of light within thevisible light spectrum in order to harvest energy for this process. Many species of cyanobacteria have light-harvesting proteins that specialize in the absorption of a small range of wavelengths oflight along the visual light spectrum; others can undergo complementary chromatic adaptation and alter these light-harvesting proteins in order to absorb the wavelengths of light that are mostavailable in a given environment. This variation in light-harvesting phenotype across cyanobacteria leads to the utilization of environmental niches based on light wavelength availability. Furthermore, light attenuation along the water column in an aquatic system also leads to the formation of environmental niches throughout the vertical water column. In order to better understand these niches based on light wavelength availability, we studied the compositionof cyanobacterial genera at the surface and depth of Lake Chillisquaque at three time points throughout the year: September 2009, May 2010, and July 2010. We found that cyanobacterialgenera composition changes throughout the year as well as with physical location in the water column. Additionally, given the light attenuation noted throughout the Lake Chillisquaque, we are able to conclude that light is a major selective factor in the community composition of Lake Chillisquaque.

Investigating the Role of System Justification in Mental Illness Stigma

The current study integrates system justification theory with research on mental illness stigma. Stereotypes of both low- and high-status groups in society can be a means of satisfying the system justification motive, or the motive to view societal inequalities as justified (as reviewed in Jost, Banaji, & Nosek, 2004). Corrigan, Watson, and Ottati (2003) proposed that system justification theory may be able to explain the origins of particular stereotypes of people with mental illness, such as dangerousness and incompetence. The primary goal of the present study was to investigate whether the stigmatization of people with mental illness – a specific form of stigmatization of a lowstatus group – can be at least partially attributed to a broader motive to justify societal inequalities. To test this, the current study included both an experimental manipulation of the perceived legitimacy of the social system and a measure of system-justifying beliefs. Stigmatization of individuals with mental illness was measured with both explicit selfreport measures (semantic differentials and the Attribution Questionnaire) and an implicit measure (a computer-based Implicit Association Test). The relationships between participant characteristics, such as personal experience with mental illness, and stigma were also investigated. Consistent with past research demonstrating only modest correlations between explicit and implicit stigma, greater self-reported fear toward a person with a chronic mental illness was weakly associated with increased implicit bias against mental illness in favor of physical disability. There was little support for the involvement of system justification in explicit stigma. Participants with personal experience with mental illness were less likely to self-report fear and avoidance of a person with a chronic mental illness. These findings have implications for stigmareduction efforts.